摘要
为了更好地解决航拍图像易受光照、旋转变化、尺度变化等影响,KAZE算法实时性较差以及基于K近邻的特征匹配算法耗时较长等问题,该文提出了一种基于改进KAZE的无人机航拍图像拼接算法.该方法首先利用加速的KAZE算法提取图像的特征点,采用二进制特征描述子FREAK (Fast rctina kcypoint)进行特征点描述,然后使用Crid-KNN算法进行特征点粗匹配,利用随机一致性算法对匹配的特征点进一步提纯并计算几何变换模型,最后采用加权平均算法对图像进行融合.实验结果表明,该文所提算法使图像在光照变化、旋转变化及尺度变化下具有较好的性能,且处理速度较KAZE算法与K近邻特征匹配算法有较大提升,是一种稳定、精确度高、拼接效果良好的无人机航拍图像拼接方法.
The aerial image is subject to many effects including light, rotation changes, changes in dimensions and so on.The real-time performance of the KAZE algorithm is not desirable and the K-nearest neighbor(KNN) match algorithm takes a long time. Therefore, we propose a mosaic algorithm for UAV aerial image based on the improved KAZE. Firstly,we use an accelerated KAZE algorithm to extract feature points of the image, and use the binary feature descriptor fast retina keypoint(FREAK) to describe the feature points. Then, we adopt the Grid-KNN algorithm for rough match of these points, and use the random sample consensus algorithm for exact match and calculating the geometric transform model. Finally, we use the weighted average algorithm for image fusion. Experimental results show that compared with the KAZE algorithm and the KNN algorithm, the proposed algorithm has better performance on changes of illumination,rotation and scale, as well as processing speed. It is a stable, accurate and stitching algorithm.
作者
韩敏
闫阔
秦国帅
HAN Min;YAN Kuo;QIN Guo-Shuai(Faculty of Electronic Information and Electrical Engineering,Dalian University of Technology,Dalian 116023;Faculty of Infrastructure Engineering,Dalian University of Technology,Dalian 116023)
出处
《自动化学报》
EI
CSCD
北大核心
2019年第2期305-314,共10页
Acta Automatica Sinica
基金
国家自然科学基金委科学仪器基础研究专项(51327004)
国家自然科学基金(61773087
61702077)
中央高校基本科研业务费(DUT17ZD216)资助~~
作者简介
通信作者:韩敏,大连理工大学电子信息与电气工程学部教授.主要研究方向为模式识别,复杂系统建模与分析及时间序列预测.E-mail:miiilian@dlut.edu.cn;闫阔,大连理工大学电子信息与电气工程学部硕士研究生.主要研究方向为图像拼接技术.E-mail:yankuo@mail.dlut.edu.cn;秦国帅,大连理工大学建设工程学部博士研究生.主要研究方向为环境水资源系统分析.E-mail:qgsl991@mail.dlut.edu.cn
